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Sexual and Gender-Diverse Individuals Face More Health Challenges during COVID-19: A Large-Scale Social Media Analysis with Natural Language Processing.

作者信息

Zhang Zhiyun, Hua Yining, Zhou Peilin, Lin Shixu, Li Minghui, Zhang Yujie, Zhou Li, Liao Yanhui, Yang Jie

机构信息

Department of Big Data in Health Science School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.

Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

出版信息

Health Data Sci. 2024 Sep 6;4:0127. doi: 10.34133/hds.0127. eCollection 2024.


DOI:10.34133/hds.0127
PMID:39247070
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11378377/
Abstract

The COVID-19 pandemic has caused a disproportionate impact on the sexual and gender-diverse (SGD) community. Compared with non-SGD populations, their social relations and health status are more vulnerable, whereas public health data regarding SGD are scarce. To analyze the concerns and health status of SGD individuals, this cohort study leveraged 471,371,477 tweets from 251,455 SGD and 22,644,411 non-SGD users, spanning from 2020 February 1 to 2022 April 30. The outcome measures comprised the distribution and dynamics of COVID-related topics, attitudes toward vaccines, and the prevalence of symptoms. Topic analysis revealed that SGD users engaged more frequently in discussions related to "friends and family" (20.5% vs. 13.1%, < 0.001) and "wear masks" (10.1% vs. 8.3%, < 0.001) compared to non-SGD users. Additionally, SGD users exhibited a marked higher proportion of positive sentiment in tweets about vaccines, including Moderna, Pfizer, AstraZeneca, and Johnson & Johnson. Among 102,464 users who self-reported COVID-19 diagnoses, SGD users disclosed significantly higher frequencies of mentioning 61 out of 69 COVID-related symptoms than non-SGD users, encompassing both physical and mental health challenges. The results provide insights into an understanding of the unique needs and experiences of the SGD community during the pandemic, emphasizing the value of social media data in epidemiological and public health research.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9106/11378377/14f877da6423/hds.0127.fig.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9106/11378377/e29afe5a9dfe/hds.0127.fig.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9106/11378377/1c0e03bbe2c3/hds.0127.fig.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9106/11378377/14f877da6423/hds.0127.fig.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9106/11378377/e29afe5a9dfe/hds.0127.fig.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9106/11378377/1c0e03bbe2c3/hds.0127.fig.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9106/11378377/14f877da6423/hds.0127.fig.003.jpg

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[1]
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[2]
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[3]
Trend and Co-occurrence Network of COVID-19 Symptoms From Large-Scale Social Media Data: Infoveillance Study.

J Med Internet Res. 2023-3-14

[4]
Assessing widening disparities in HbA1c and systolic blood pressure retesting during the COVID-19 pandemic in an LGBTQ+-focused federally qualified health center in Chicago: a retrospective cohort study using electronic health records.

BMJ Open Diabetes Res Care. 2022-12

[5]
Data-driven identification of post-acute SARS-CoV-2 infection subphenotypes.

Nat Med. 2023-1

[6]
Tracking the Impact of COVID-19 and Lockdown Policies on Public Mental Health Using Social Media: Infoveillance Study.

J Med Internet Res. 2022-10-13

[7]
COVID Symptoms, Symptom Clusters, and Predictors for Becoming a Long-Hauler Looking for Clarity in the Haze of the Pandemic.

Clin Nurs Res. 2022-11

[8]
Using Twitter data to understand public perceptions of approved versus off-label use for COVID-19-related medications.

J Am Med Inform Assoc. 2022-9-12

[9]
Rapid, application-based survey to characterise the impacts of COVID-19 on LGBTQ+ communities around the world: an observational study.

BMJ Open. 2022-4-12

[10]
Mental health impacts of the COVID-19 pandemic on college students.

J Am Coll Health. 2024

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